HEART-felt Narratives: Tracing Empathy and Narrative Style in Personal Stories with LLMs

January 1, 2024Open Access

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Key Points

The study aims to explore how narrative style influences empathy in personal stories, using large language models.
Empirical examination of the relationship between narrative style and empathy through LLMs and crowdsourcing.
Introduction of HEART taxonomy to identify narrative elements linked to empathy.
Dataset collection involving empathy judgments from 2,624 participants.
Narrative elements like emotional vividness and plot volume significantly contribute to empathy, with LLMs providing human-level annotations.
HEART taxonomy enhances the understanding of how storytelling style can evoke empathy.
Findings indicate the potential of LLMs for narrative analyses, leading to behavioral insights.

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Examines the relationship between narrative style and empathy in personal stories, suggesting implications for social insights.

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Shen et al. (2024) studied this question.

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